yes keep Chapter 2, 3, 4, 6, 7, 8 and let’s consider our audience software architects looking to create solutions for corporations. They are power sys-admins and swe developers that should be using orchestration and data driven dynamic prompts to facilitate their own work and the company and ultimately clients. my proposition is that any technical power users should be using n8n or make.com and have keys for openai and claude at least, and be combining llm api requests into complex workflows. for example, rows of urls in a google sheet, n8n gets the urls, calls a python script to scrape the url, passes the result through an openai summarizer node, passes that through a research the summary openai request returning a structured response, then cycles through the research results making queries for original content on the combined research and summary. Then one more pass of the original content through openai request to format to html. that is 4 openai requests for one piece of semi-original content. in order to add variety to our results we need dynamic modifiers. this is where dynamic prompts and variables comes in. we have a database of types of everything, colors links to 40 colors, pastel-colors, links to 40 pastel colors. And on for everything, types of cars, descriptions of Canada, art styles, font familes, etc, etc. the actual system and user message sent to openai api is a multi-stage constructed work of art, half generated by AI itself. This is level of prompt solutions this book reader should understand. the n8n example should be one of similar use case studies. Another example i want to explore in the book is the facilitator prompt or a prompt that analyzes the user prompt and breaks it down into subtasks, then runs those subtasks. We will teach early about system and user message types in openai and structured responses vs the default which is less predictable. I want the first chapter of the book to be realistic, specific use cases professional workers and owners could use AI pipelines. so really this book is about AI solution engineering, for individuals and companies, but the heart of LLM solutions is the prompt.